Conference on "Statistical Methods for Complex Biomedical Data"

描述(申请人提供)：定量方法在设计和分析基础科学、癌症研究中的观察性和随机性研究，以及更广泛的健康科学研究中变得越来越重要。现代生物医学研究已经变得更加跨学科。随着生物技术的快速发展和海量生物医学数据的日益复杂，特别是在基因组学和蛋白质组学中，出现了大量具有挑战性的统计和计算问题。传统的统计技术不能满足这些新的需求，导致越来越需要开发创新的统计和计算方法来解决这些在分析大型和复杂的生物医学数据集时出现的问题。因此，拥有一个生物统计学家和科学家可以批评现有方法、介绍和讨论已开发的创新新方法并确定未来研究优先事项的平台将是非常有价值的。为了响应这种需求，我们提出了一个名为《复杂生物医学数据的统计方法》的会议，该会议将涵盖癌症研究和一般生物医学研究的关键主题，包括营养流行病学、测量误差模型、非参数和半参数推断、功能数据分析、计算生物学和遗传流行病学。这次会议将为定量和生物医学研究人员提供一个促进跨学科互动的场所。会议将在德克萨斯州大学站的德克萨斯农工大学举行，那里有一个领先的统计系。为了加强宣传，并允许最大限度的参观者，它将安排在2009年在德克萨斯州圣安东尼奥举行的国际生物识别学会东北美地区会议之前举行。其具体目标是“提供一个及时和鼓舞人心的平台，让生物统计学家、定量研究人员和生物医学科学家参与对新出现的统计和计算问题的前沿深入讨论，特别是在计算生物学和遗传流行病学、营养流行病学、测量误差、非参数和半参数回归方法以及功能数据分析方法等领域。”促进和促进跨学科研究，并将讨论和结果传播给定量和主题生物医学研究人员，并吸引初级研究人员参与这些问题。 与公共卫生的相关性：随着生物技术的快速发展和生物医学研究产生的数据的日益复杂，癌症研究和一般生物医学研究中出现的量化挑战越来越多，必须成功地解决这些挑战才能取得进展。生物统计学研究人员正在努力通过开发和传播这些领域所需的新的统计方法来应对这些挑战。在这笔赠款中，我们提出了一个名为“复杂生物医学数据的统计方法”的会议，在这个会议上，我们组织了一些生物统计学的顶尖研究人员聚集在一起，提出了几个对癌症研究具有及时重要性的关键领域的重要前沿量化工作，并为高级和初级研究人员、定量和主题生物医学研究人员提供了一个参与这些问题的平台。

DESCRIPTION (provided by applicant): Quantitative methods have become increasingly important in the design and analysis of basic science, observational and randomized studies in cancer research, and health sciences research more generally. Modern biomedical research has become much more interdisciplinary. With the rapid advance of biotechnology and growing complexity of massive biomedical data, especially in genomics and proteomics, a significant number of challenging statistical and computational issues have emerged. Traditional statistical techniques cannot meet these new demands, leading to an increasing need to develop innovative statistical and computational methods to address these emerging issues in analyzing large and complex biomedical data sets. It would therefore be very valuable to have a platform in which biostatisticians and scientists can critique existing methods, present and discuss innovative new methods that have been developed, and identify priorities for future research. To respond to such a need, we propose a conference "Statistical Methods for Complex Biomedical Data", which would cover topics crucial to cancer research, and biomedical research in general, including nutritional epidemiology, measurement error models, nonparametric and semiparametric inference, functional data analysis, computational biology, and genetic epidemiology. This conference would provide quantitative and biomedical researchers a venue for stimulating interdisciplinary interaction. The Conference will be held at Texas A&M University in College Station, Texas, which houses a leading Statistics department. To increase its publicity and allow maximal attendance, it will be scheduled to take place just before the East North American Region meetings of the International Biometric Society which are in San Antonio, Texas in 2009. The specific aims are "To provide a timely and stimulating platform to engage biostatisticians, quantitative researchers, and biomedical scientists in cutting-edge in-depth discussions of emerging statistical and computational issues, especially in the areas of computational biology and genetic epidemiology, nutritional epidemiology, measurement error, nonparametric and semiparametric regression methods, and methods to analyze functional data. "To promote and foster interdisciplinary research and disseminate the discussions and the results to quantitative and subject-matter biomedical researchers, and engage junior investigators in these issues. Public Health Relevance: With the rapid advance of biotechnology and the increasing complexity of the data generated by biomedical studies, there are growing quantitative challenges that arise in cancer research, and biomedical research in general, that must be successfully addressed in order to make progress. Biostatistical researchers are working to address these challenges by developing and disseminating new statistical methodology that is needed in these fields. In this grant, we propose a conference "Statistical Methods for Complex Biomedical Data", in which we organize some of the top researchers in biostatistics to come together and present important cutting edge quantitative work in several key areas that are timely important for cancer research, and providing a platform for senior and junior investigators, quantitative and subject-matter biomedical researchers to engage in these issues.